## Prerequisites

- Linux or macOS
- Python 3.6+
- PyTorch 1.3+
- CUDA 9.2+ (If you build PyTorch from source, CUDA 9.0 is also compatible)
- GCC 5+
- [MMCV](https://mmcv.readthedocs.io/en/latest/get_started/installation.html)
- [MMDetection](https://mmdetection.readthedocs.io/en/latest/get_started.html#installation)

The compatible MMTracking, MMCV, and MMDetection versions are as below. Please install the correct version to avoid installation issues.

|  MMTracking version |       MMCV version       |      MMDetection version      |
|:-------------------:|:------------------------:|:-----------------------------:|
|        master       | mmcv-full>=1.3.8, <1.4.0 |       MMDetection>=2.14.0      |
|        0.6.0        | mmcv-full>=1.3.8, <1.4.0 |       MMDetection>=2.14.0     |
|        0.7.0        | mmcv-full>=1.3.8, <1.4.0 |       MMDetection>=2.14.0     |
|        0.8.0        | mmcv-full>=1.3.8, <1.4.0 |       MMDetection>=2.14.0     |

## Installation

### Detailed Instructions

1. Create a conda virtual environment and activate it.

    ```shell
    conda create -n open-mmlab python=3.7 -y
    conda activate open-mmlab
    ```

2. Install PyTorch and torchvision following the [official instructions](https://pytorch.org/), e.g.,

    ```shell
    conda install pytorch torchvision -c pytorch
    ```

    Note: Make sure that your compilation CUDA version and runtime CUDA version match.
    You can check the supported CUDA version for precompiled packages on the [PyTorch website](https://pytorch.org/).

    `E.g.1` If you have CUDA 10.1 installed under `/usr/local/cuda` and would like to install
    PyTorch 1.5, you need to install the prebuilt PyTorch with CUDA 10.1.

    ```shell
    conda install pytorch==1.5 cudatoolkit=10.1 torchvision -c pytorch
    ```

    `E.g. 2` If you have CUDA 9.2 installed under `/usr/local/cuda` and would like to install
    PyTorch 1.3.1., you need to install the prebuilt PyTorch with CUDA 9.2.

    ```shell
    conda install pytorch=1.3.1 cudatoolkit=9.2 torchvision=0.4.2 -c pytorch
    ```

    If you build PyTorch from source instead of installing the prebuilt pacakge,
    you can use more CUDA versions such as 9.0.

3. Install mmcv-full, we recommend you to install the pre-build package as below.

    ```shell
    pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.6.0/index.html
    ```

    See [here](https://mmcv.readthedocs.io/en/latest/get_started/installation.html) for different versions of MMCV compatible to different PyTorch and CUDA versions.
    Optionally you can choose to compile mmcv from source by the following command

    ```shell
    git clone https://github.com/open-mmlab/mmcv.git
    cd mmcv
    MMCV_WITH_OPS=1 pip install -e .  # package mmcv-full will be installed after this step
    cd ..
    ```

    Or directly run

    ```shell
    pip install mmcv-full
    ```

4. Install MMDetection

    ```shell
    pip install mmdet
    ```

    Optionally, you can also build MMDetection from source in case you want to modify the code:

    ```shell
    git clone https://github.com/open-mmlab/mmdetection.git
    cd mmdetection
    pip install -r requirements/build.txt
    pip install -v -e .  # or "python setup.py develop"
    ```

5. Clone the MMTracking repository.

    ```shell
    git clone https://github.com/open-mmlab/mmtracking.git
    cd mmtracking
    ```

6. Install build requirements and then install MMTracking.

    ```shell
    pip install -r requirements/build.txt
    pip install -v -e .  # or "python setup.py develop"
    ```

Note:

a. Following the above instructions, MMTracking is installed on `dev` mode
, any local modifications made to the code will take effect without the need to reinstall it.

b. If you would like to use `opencv-python-headless` instead of `opencv-python`,
you can install it before installing MMCV.

### A from-scratch setup script

Assuming that you already have CUDA 10.1 installed, here is a full script for setting up MMTracking with conda.

```shell
conda create -n open-mmlab python=3.7 -y
conda activate open-mmlab

conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.1 -c pytorch -y

# install the latest mmcv
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.6.0/index.html

# install mmdetection
pip install mmdet

# install mmtracking
git clone https://github.com/open-mmlab/mmtracking.git
cd mmtracking
pip install -r requirements/build.txt
pip install -v -e .
```

### Developing with multiple MMTracking versions

The train and test scripts already modify the `PYTHONPATH` to ensure the script use the MMTracking in the current directory.

To use the default MMTracking installed in the environment rather than that you are working with, you can remove the following line in those scripts

```shell
PYTHONPATH="$(dirname $0)/..":$PYTHONPATH
```

## Verification

To verify whether MMTracking and the required environment are installed correctly, we can run MOT, VID, SOT demo script.

For example, run MOT demo and you will see a output video named `mot.mp4`:

```shell
python demo/demo_mot.py configs/mot/deepsort/sort_faster-rcnn_fpn_4e_mot17-private.py --input demo/demo.mp4 --output mot.mp4
```